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In situ asymmetric island sidewall growth (AISG) was developed to enhance Ga-face facet growth and improve the crystalline quality of (1122) GaN epilayers on m-plane sapphire substrates. In the early growth stage island shaping and sidewall faceting were distinct and controlled by growth design. Using in situ AISG, {0002} instead of {1103} sidewall facets were formed on the Ga-rich island surface, which eliminated formation of a {1103} phase during subsequent layer growth of semipolar GaN. Enhanced Ga-face sidewall facet growth led to +c regions overlapping −c regions, which reduced defect density. Pure semipolar (1122) epilayers with a reduced surface striation density and a basal-plane stacking fault density of 8 × 10 3 cm −1 were obtained. The observation of a narrow E H 2 peak and an intense E 1 (LO) peak in Raman spectra indicates that almost strain-free high-quality semipolar (1122) GaN films were achieved. The photoluminescence emission intensity from the (1122) GaN film prepared by in situ AISG was dominated by band-edge emission and enhanced ∼4 times more than that from conventional (1122) GaN.

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Linear secret-sharing scheme (LSSS) is a useful tool for supporting flexible access policy in building attribute-based encryption (ABE) schemes. But in lattice-based ABE constructions, there is a subtle security problem in the sense that careless usage of LSSS-based secret sharing over vectors would lead to the leakage of the master secret key. In this paper, we propose a new method that employs LSSS to build lattice-based key-policy attribute-based encryption (KP-ABE) that resolves this security issue. More specifically, no adversary can reconstruct the master secret key since we introduce a new trapdoor generation algorithm to generate a strong trapdoor (instead of a lattice basis), that is, the master secret key, and remove the dependency of the master secret key on the total number of system attributes. Meanwhile, with the purpose of reducing the storage cost and support dynamic updating on attributes, we extended the traditional 1-dimensional attribute structure to 2-dimensional one. This makes our construction remarkably efficient in space cost, with acceptable time cost. Finally, our scheme is proved to be secure in the standard model.